Giga Computing has unveiled GAIFA, its first proprietary AI computing center, with an initial planned power capacity of 700 kW in New Taipei City, Taiwan.

The six-rack facility is designed as a real-world validation environment for data-center infrastructure. It brings compute, storage, high-speed networking, direct liquid cooling and power together so customers can test complete rack-scale systems before larger deployments.

Two GB300 NVL72 racks anchor the facility

GAIFA starts with two NVIDIA GB300 NVL72 racks plus a G4L4-SD3-LAX7 direct-liquid-cooled server rack using NVIDIA HGX B300. Additional platforms include NVIDIA RTX PRO 6000 GPUs and liquid-cooled AMD EPYC systems.

The embedded video is from Giga Computing and is in English. GAIFA is intended to validate training, inference and professional visualization workloads while measuring GPU and CPU throughput, rack power density, liquid-cooling performance, thermal management, network performance and system compatibility.

Full-stack validation before deployment

Giga Computing says the facility extends its role from server manufacturing into integrated AI infrastructure. The company can test how servers behave with the facility’s electricity, cooling, software and IT systems before customers deploy them at scale.

Networking is part of that validation. Giga’s broader GAIFA architecture includes NVIDIA Quantum-X800 InfiniBand and Spectrum-X Ethernet, while the physical facility tests east-west network performance alongside compute and cooling.

700 kW is only the first phase

The initial phase is planned for 700 kW, with additional capacity planned as operational needs develop. That makes GAIFA smaller than hyperscale AI campuses but useful as an engineering proving ground where dense racks can be validated before replication across much larger facilities.

BitcoinVersus.tech has recently covered the same infrastructure convergence through ABB’s 800 VDC AI power architecture, Supermicro’s Vera Rubin NVL72 systems, and Synopsys and TSMC’s advanced AI-chip design stack.

Sources: Giga Computing and StorageReview.

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